{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, sys\n",
    "import time\n",
    "import datetime\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import math\n",
    "from math import radians, cos, sin, asin, sqrt \n",
    "import random\n",
    "\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MultipleLocator, FormatStrFormatter\n",
    "from matplotlib.patches import Ellipse, Circle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_bkg(sw,ne):\n",
    "    \n",
    "    '''Initial parameter'''\n",
    "    bg_path='Chengdu.png'\n",
    "    \n",
    "    '''Figure out'''\n",
    "    img = plt.imread(bg_path)\n",
    "    height, width = img.shape[:2]\n",
    "    h1 = math.ceil(10./width*height)\n",
    "    fig = plt.figure(figsize=(10,h1))\n",
    "    ax = fig.add_subplot(111)\n",
    "    xgrange, ygrange = ((sw[1], ne[1]), (sw[0], ne[0]))\n",
    "    plt.xlim(xgrange)\n",
    "    plt.ylim(ygrange)\n",
    "    x0,x1 = ax.get_xlim()\n",
    "    y0,y1 = ax.get_ylim()\n",
    "    plt.xticks(np.arange(xgrange[0], xgrange[1], 0.352/15))\n",
    "    plt.yticks(np.arange(ygrange[0], ygrange[1], 0.2415/13))\n",
    "    try:\n",
    "        ax.imshow(img, extent=[x0, x1, y0, y1], aspect='auto', alpha=.5)\n",
    "    except:\n",
    "        pass\n",
    "    return fig, ax, xgrange, ygrange\n",
    "\n",
    "\n",
    "\n",
    "'''Time stamp'''\n",
    "def stamp_transit(time_str):\n",
    "    timeArray = time.strptime(time_str, \"%Y-%m-%d %H:%M:%S\")\n",
    "    timeStamp = int(time.mktime(timeArray))\n",
    "    return timeStamp\n",
    "    \n",
    "'''Time step'''\n",
    "\n",
    "def stamp_to_step(timestamp,date_str,step):\n",
    "    baseline = date_str+\" 00:00:00\";\n",
    "    baseline = int(stamp_transit(baseline))\n",
    "    current_step=int((timestamp-baseline)/step)\n",
    "    return current_step"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Grid spatial Ranges"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Grid_id</th>\n",
       "      <th>v1_lng</th>\n",
       "      <th>v1_lat</th>\n",
       "      <th>v2_lng</th>\n",
       "      <th>v2_lat</th>\n",
       "      <th>v3_lng</th>\n",
       "      <th>v3_lat</th>\n",
       "      <th>v4_lng</th>\n",
       "      <th>v4_lat</th>\n",
       "      <th>v5_lng</th>\n",
       "      <th>v5_lat</th>\n",
       "      <th>v6_lng</th>\n",
       "      <th>v6_lat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>c151c79af5585f6a</td>\n",
       "      <td>104.46545</td>\n",
       "      <td>30.87166</td>\n",
       "      <td>104.46959</td>\n",
       "      <td>30.87584</td>\n",
       "      <td>104.46756</td>\n",
       "      <td>30.88151</td>\n",
       "      <td>104.46139</td>\n",
       "      <td>30.88301</td>\n",
       "      <td>104.45725</td>\n",
       "      <td>30.87883</td>\n",
       "      <td>104.45927</td>\n",
       "      <td>30.87316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3a1ce6f60c8696eb</td>\n",
       "      <td>103.60379</td>\n",
       "      <td>30.82045</td>\n",
       "      <td>103.60784</td>\n",
       "      <td>30.82462</td>\n",
       "      <td>103.60577</td>\n",
       "      <td>30.83025</td>\n",
       "      <td>103.59966</td>\n",
       "      <td>30.83170</td>\n",
       "      <td>103.59562</td>\n",
       "      <td>30.82752</td>\n",
       "      <td>103.59769</td>\n",
       "      <td>30.82190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>aada8f5ae067d90a</td>\n",
       "      <td>104.17495</td>\n",
       "      <td>30.50817</td>\n",
       "      <td>104.17904</td>\n",
       "      <td>30.51233</td>\n",
       "      <td>104.17701</td>\n",
       "      <td>30.51798</td>\n",
       "      <td>104.17088</td>\n",
       "      <td>30.51947</td>\n",
       "      <td>104.16679</td>\n",
       "      <td>30.51531</td>\n",
       "      <td>104.16882</td>\n",
       "      <td>30.50966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4375f4117407765f</td>\n",
       "      <td>103.66009</td>\n",
       "      <td>30.95611</td>\n",
       "      <td>103.66415</td>\n",
       "      <td>30.96029</td>\n",
       "      <td>103.66208</td>\n",
       "      <td>30.96592</td>\n",
       "      <td>103.65596</td>\n",
       "      <td>30.96737</td>\n",
       "      <td>103.65190</td>\n",
       "      <td>30.96319</td>\n",
       "      <td>103.65397</td>\n",
       "      <td>30.95756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2bc0e4d5556e7b48</td>\n",
       "      <td>104.00960</td>\n",
       "      <td>30.96582</td>\n",
       "      <td>104.01370</td>\n",
       "      <td>30.97000</td>\n",
       "      <td>104.01164</td>\n",
       "      <td>30.97565</td>\n",
       "      <td>104.00550</td>\n",
       "      <td>30.97711</td>\n",
       "      <td>104.00140</td>\n",
       "      <td>30.97293</td>\n",
       "      <td>104.00345</td>\n",
       "      <td>30.96728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ace3bb4a658ef318</td>\n",
       "      <td>104.63357</td>\n",
       "      <td>30.74776</td>\n",
       "      <td>104.63773</td>\n",
       "      <td>30.75193</td>\n",
       "      <td>104.63571</td>\n",
       "      <td>30.75761</td>\n",
       "      <td>104.62954</td>\n",
       "      <td>30.75912</td>\n",
       "      <td>104.62538</td>\n",
       "      <td>30.75495</td>\n",
       "      <td>104.62740</td>\n",
       "      <td>30.74927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>e3c98397598c1c76</td>\n",
       "      <td>103.98500</td>\n",
       "      <td>30.98716</td>\n",
       "      <td>103.98909</td>\n",
       "      <td>30.99134</td>\n",
       "      <td>103.98704</td>\n",
       "      <td>30.99699</td>\n",
       "      <td>103.98089</td>\n",
       "      <td>30.99845</td>\n",
       "      <td>103.97680</td>\n",
       "      <td>30.99427</td>\n",
       "      <td>103.97885</td>\n",
       "      <td>30.98862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ae1f2fa6c175a64a</td>\n",
       "      <td>103.90827</td>\n",
       "      <td>30.33643</td>\n",
       "      <td>103.91232</td>\n",
       "      <td>30.34058</td>\n",
       "      <td>103.91028</td>\n",
       "      <td>30.34621</td>\n",
       "      <td>103.90419</td>\n",
       "      <td>30.34769</td>\n",
       "      <td>103.90014</td>\n",
       "      <td>30.34354</td>\n",
       "      <td>103.90218</td>\n",
       "      <td>30.33791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>dcee410b6fe3282e</td>\n",
       "      <td>103.44397</td>\n",
       "      <td>30.21340</td>\n",
       "      <td>103.44797</td>\n",
       "      <td>30.21755</td>\n",
       "      <td>103.44591</td>\n",
       "      <td>30.22315</td>\n",
       "      <td>103.43986</td>\n",
       "      <td>30.22461</td>\n",
       "      <td>103.43587</td>\n",
       "      <td>30.22047</td>\n",
       "      <td>103.43793</td>\n",
       "      <td>30.21486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5271bff5de1ffc6e</td>\n",
       "      <td>104.13052</td>\n",
       "      <td>30.89558</td>\n",
       "      <td>104.13463</td>\n",
       "      <td>30.89976</td>\n",
       "      <td>104.13258</td>\n",
       "      <td>30.90541</td>\n",
       "      <td>104.12643</td>\n",
       "      <td>30.90689</td>\n",
       "      <td>104.12232</td>\n",
       "      <td>30.90271</td>\n",
       "      <td>104.12437</td>\n",
       "      <td>30.89706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>23ab47ea30b86a2e</td>\n",
       "      <td>104.00961</td>\n",
       "      <td>30.91938</td>\n",
       "      <td>104.01371</td>\n",
       "      <td>30.92356</td>\n",
       "      <td>104.01166</td>\n",
       "      <td>30.92921</td>\n",
       "      <td>104.00551</td>\n",
       "      <td>30.93068</td>\n",
       "      <td>104.00142</td>\n",
       "      <td>30.92650</td>\n",
       "      <td>104.00347</td>\n",
       "      <td>30.92085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>efab0dee4b2e5d4b</td>\n",
       "      <td>104.05878</td>\n",
       "      <td>30.92310</td>\n",
       "      <td>104.06288</td>\n",
       "      <td>30.92728</td>\n",
       "      <td>104.06084</td>\n",
       "      <td>30.93293</td>\n",
       "      <td>104.05469</td>\n",
       "      <td>30.93440</td>\n",
       "      <td>104.05059</td>\n",
       "      <td>30.93022</td>\n",
       "      <td>104.05264</td>\n",
       "      <td>30.92457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>d5905a7da4f635ce</td>\n",
       "      <td>103.55088</td>\n",
       "      <td>30.50996</td>\n",
       "      <td>103.55490</td>\n",
       "      <td>30.51412</td>\n",
       "      <td>103.55284</td>\n",
       "      <td>30.51974</td>\n",
       "      <td>103.54676</td>\n",
       "      <td>30.52120</td>\n",
       "      <td>103.54274</td>\n",
       "      <td>30.51704</td>\n",
       "      <td>103.54480</td>\n",
       "      <td>30.51142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4041553b7ed092e6</td>\n",
       "      <td>103.81641</td>\n",
       "      <td>30.54362</td>\n",
       "      <td>103.82046</td>\n",
       "      <td>30.54778</td>\n",
       "      <td>103.81841</td>\n",
       "      <td>30.55341</td>\n",
       "      <td>103.81231</td>\n",
       "      <td>30.55489</td>\n",
       "      <td>103.80826</td>\n",
       "      <td>30.55072</td>\n",
       "      <td>103.81030</td>\n",
       "      <td>30.54509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>f1b6c8117696673e</td>\n",
       "      <td>103.53234</td>\n",
       "      <td>30.56051</td>\n",
       "      <td>103.53636</td>\n",
       "      <td>30.56467</td>\n",
       "      <td>103.53430</td>\n",
       "      <td>30.57029</td>\n",
       "      <td>103.52821</td>\n",
       "      <td>30.57174</td>\n",
       "      <td>103.52419</td>\n",
       "      <td>30.56758</td>\n",
       "      <td>103.52625</td>\n",
       "      <td>30.56196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7e9ff7da4f408d2e</td>\n",
       "      <td>103.59068</td>\n",
       "      <td>30.28020</td>\n",
       "      <td>103.59469</td>\n",
       "      <td>30.28435</td>\n",
       "      <td>103.59264</td>\n",
       "      <td>30.28996</td>\n",
       "      <td>103.58658</td>\n",
       "      <td>30.29143</td>\n",
       "      <td>103.58256</td>\n",
       "      <td>30.28728</td>\n",
       "      <td>103.58462</td>\n",
       "      <td>30.28167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>e8c28e64215c5e9c</td>\n",
       "      <td>103.94641</td>\n",
       "      <td>30.70777</td>\n",
       "      <td>103.95048</td>\n",
       "      <td>30.71194</td>\n",
       "      <td>103.94843</td>\n",
       "      <td>30.71758</td>\n",
       "      <td>103.94231</td>\n",
       "      <td>30.71905</td>\n",
       "      <td>103.93823</td>\n",
       "      <td>30.71488</td>\n",
       "      <td>103.94028</td>\n",
       "      <td>30.70924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>04f385c0c65f3215</td>\n",
       "      <td>104.06694</td>\n",
       "      <td>30.82311</td>\n",
       "      <td>104.07104</td>\n",
       "      <td>30.82728</td>\n",
       "      <td>104.06899</td>\n",
       "      <td>30.83293</td>\n",
       "      <td>104.06285</td>\n",
       "      <td>30.83441</td>\n",
       "      <td>104.05876</td>\n",
       "      <td>30.83023</td>\n",
       "      <td>104.06080</td>\n",
       "      <td>30.82458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>e12ab567c78183b0</td>\n",
       "      <td>103.54363</td>\n",
       "      <td>30.37857</td>\n",
       "      <td>103.54765</td>\n",
       "      <td>30.38272</td>\n",
       "      <td>103.54559</td>\n",
       "      <td>30.38833</td>\n",
       "      <td>103.53952</td>\n",
       "      <td>30.38980</td>\n",
       "      <td>103.53551</td>\n",
       "      <td>30.38564</td>\n",
       "      <td>103.53756</td>\n",
       "      <td>30.38003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>80a4533cbfb9b099</td>\n",
       "      <td>103.87344</td>\n",
       "      <td>30.49388</td>\n",
       "      <td>103.87750</td>\n",
       "      <td>30.49804</td>\n",
       "      <td>103.87545</td>\n",
       "      <td>30.50367</td>\n",
       "      <td>103.86935</td>\n",
       "      <td>30.50515</td>\n",
       "      <td>103.86529</td>\n",
       "      <td>30.50099</td>\n",
       "      <td>103.86734</td>\n",
       "      <td>30.49536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9358fc61e324214c</td>\n",
       "      <td>103.77518</td>\n",
       "      <td>30.71797</td>\n",
       "      <td>103.77923</td>\n",
       "      <td>30.72214</td>\n",
       "      <td>103.77718</td>\n",
       "      <td>30.72778</td>\n",
       "      <td>103.77107</td>\n",
       "      <td>30.72924</td>\n",
       "      <td>103.76701</td>\n",
       "      <td>30.72507</td>\n",
       "      <td>103.76906</td>\n",
       "      <td>30.71944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0fce32b720c091ba</td>\n",
       "      <td>104.10786</td>\n",
       "      <td>30.78747</td>\n",
       "      <td>104.11196</td>\n",
       "      <td>30.79164</td>\n",
       "      <td>104.10992</td>\n",
       "      <td>30.79729</td>\n",
       "      <td>104.10378</td>\n",
       "      <td>30.79877</td>\n",
       "      <td>104.09968</td>\n",
       "      <td>30.79460</td>\n",
       "      <td>104.10172</td>\n",
       "      <td>30.78895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11e8bf5e1126df77</td>\n",
       "      <td>104.05455</td>\n",
       "      <td>30.34700</td>\n",
       "      <td>104.05862</td>\n",
       "      <td>30.35115</td>\n",
       "      <td>104.05658</td>\n",
       "      <td>30.35680</td>\n",
       "      <td>104.05048</td>\n",
       "      <td>30.35829</td>\n",
       "      <td>104.04641</td>\n",
       "      <td>30.35414</td>\n",
       "      <td>104.04845</td>\n",
       "      <td>30.34849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>46d449c158d95069</td>\n",
       "      <td>104.70591</td>\n",
       "      <td>30.76636</td>\n",
       "      <td>104.71008</td>\n",
       "      <td>30.77053</td>\n",
       "      <td>104.70806</td>\n",
       "      <td>30.77621</td>\n",
       "      <td>104.70189</td>\n",
       "      <td>30.77773</td>\n",
       "      <td>104.69772</td>\n",
       "      <td>30.77356</td>\n",
       "      <td>104.69974</td>\n",
       "      <td>30.76787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>5d9a1dd89fb6fa1e</td>\n",
       "      <td>103.76949</td>\n",
       "      <td>30.59601</td>\n",
       "      <td>103.77355</td>\n",
       "      <td>30.60017</td>\n",
       "      <td>103.77149</td>\n",
       "      <td>30.60580</td>\n",
       "      <td>103.76539</td>\n",
       "      <td>30.60727</td>\n",
       "      <td>103.76134</td>\n",
       "      <td>30.60311</td>\n",
       "      <td>103.76339</td>\n",
       "      <td>30.59748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7f0d5628a0368424</td>\n",
       "      <td>104.53587</td>\n",
       "      <td>30.61106</td>\n",
       "      <td>104.54000</td>\n",
       "      <td>30.61523</td>\n",
       "      <td>104.53799</td>\n",
       "      <td>30.62090</td>\n",
       "      <td>104.53183</td>\n",
       "      <td>30.62241</td>\n",
       "      <td>104.52769</td>\n",
       "      <td>30.61825</td>\n",
       "      <td>104.52971</td>\n",
       "      <td>30.61257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ce3c8255c6db1c58</td>\n",
       "      <td>103.97325</td>\n",
       "      <td>30.32572</td>\n",
       "      <td>103.97731</td>\n",
       "      <td>30.32987</td>\n",
       "      <td>103.97527</td>\n",
       "      <td>30.33551</td>\n",
       "      <td>103.96918</td>\n",
       "      <td>30.33699</td>\n",
       "      <td>103.96512</td>\n",
       "      <td>30.33285</td>\n",
       "      <td>103.96716</td>\n",
       "      <td>30.32721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>c6f4de53556ead29</td>\n",
       "      <td>103.95826</td>\n",
       "      <td>31.09155</td>\n",
       "      <td>103.96236</td>\n",
       "      <td>31.09574</td>\n",
       "      <td>103.96030</td>\n",
       "      <td>31.10138</td>\n",
       "      <td>103.95414</td>\n",
       "      <td>31.10284</td>\n",
       "      <td>103.95005</td>\n",
       "      <td>31.09865</td>\n",
       "      <td>103.95210</td>\n",
       "      <td>31.09301</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>42453274fd5765cf</td>\n",
       "      <td>103.86901</td>\n",
       "      <td>30.65948</td>\n",
       "      <td>103.87308</td>\n",
       "      <td>30.66364</td>\n",
       "      <td>103.87103</td>\n",
       "      <td>30.66928</td>\n",
       "      <td>103.86492</td>\n",
       "      <td>30.67075</td>\n",
       "      <td>103.86085</td>\n",
       "      <td>30.66658</td>\n",
       "      <td>103.86290</td>\n",
       "      <td>30.66094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>f44d5e1b125f00d4</td>\n",
       "      <td>104.41532</td>\n",
       "      <td>30.72851</td>\n",
       "      <td>104.41945</td>\n",
       "      <td>30.73268</td>\n",
       "      <td>104.41742</td>\n",
       "      <td>30.73835</td>\n",
       "      <td>104.41127</td>\n",
       "      <td>30.73985</td>\n",
       "      <td>104.40714</td>\n",
       "      <td>30.73568</td>\n",
       "      <td>104.40916</td>\n",
       "      <td>30.73001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8489</th>\n",
       "      <td>277fc8734f3b2275</td>\n",
       "      <td>104.30071</td>\n",
       "      <td>30.82874</td>\n",
       "      <td>104.30483</td>\n",
       "      <td>30.83291</td>\n",
       "      <td>104.30279</td>\n",
       "      <td>30.83858</td>\n",
       "      <td>104.29664</td>\n",
       "      <td>30.84007</td>\n",
       "      <td>104.29251</td>\n",
       "      <td>30.83589</td>\n",
       "      <td>104.29455</td>\n",
       "      <td>30.83023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8490</th>\n",
       "      <td>90f57efc5a53dedc</td>\n",
       "      <td>103.96234</td>\n",
       "      <td>31.11122</td>\n",
       "      <td>103.96644</td>\n",
       "      <td>31.11541</td>\n",
       "      <td>103.96438</td>\n",
       "      <td>31.12106</td>\n",
       "      <td>103.95823</td>\n",
       "      <td>31.12252</td>\n",
       "      <td>103.95413</td>\n",
       "      <td>31.11833</td>\n",
       "      <td>103.95619</td>\n",
       "      <td>31.11268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8491</th>\n",
       "      <td>863d22e913a49b9c</td>\n",
       "      <td>104.11370</td>\n",
       "      <td>30.49217</td>\n",
       "      <td>104.11779</td>\n",
       "      <td>30.49632</td>\n",
       "      <td>104.11575</td>\n",
       "      <td>30.50197</td>\n",
       "      <td>104.10964</td>\n",
       "      <td>30.50346</td>\n",
       "      <td>104.10555</td>\n",
       "      <td>30.49930</td>\n",
       "      <td>104.10759</td>\n",
       "      <td>30.49366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8492</th>\n",
       "      <td>1c81beefb29ff1d4</td>\n",
       "      <td>104.33066</td>\n",
       "      <td>30.60438</td>\n",
       "      <td>104.33477</td>\n",
       "      <td>30.60854</td>\n",
       "      <td>104.33274</td>\n",
       "      <td>30.61420</td>\n",
       "      <td>104.32660</td>\n",
       "      <td>30.61570</td>\n",
       "      <td>104.32249</td>\n",
       "      <td>30.61154</td>\n",
       "      <td>104.32452</td>\n",
       "      <td>30.60588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8493</th>\n",
       "      <td>9ddd02e4ffe66799</td>\n",
       "      <td>103.41965</td>\n",
       "      <td>30.23460</td>\n",
       "      <td>103.42365</td>\n",
       "      <td>30.23874</td>\n",
       "      <td>103.42159</td>\n",
       "      <td>30.24435</td>\n",
       "      <td>103.41554</td>\n",
       "      <td>30.24580</td>\n",
       "      <td>103.41155</td>\n",
       "      <td>30.24166</td>\n",
       "      <td>103.41360</td>\n",
       "      <td>30.23605</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8494</th>\n",
       "      <td>49e984f65860bbc4</td>\n",
       "      <td>104.61257</td>\n",
       "      <td>30.69587</td>\n",
       "      <td>104.61672</td>\n",
       "      <td>30.70003</td>\n",
       "      <td>104.61471</td>\n",
       "      <td>30.70571</td>\n",
       "      <td>104.60854</td>\n",
       "      <td>30.70722</td>\n",
       "      <td>104.60439</td>\n",
       "      <td>30.70306</td>\n",
       "      <td>104.60641</td>\n",
       "      <td>30.69738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8495</th>\n",
       "      <td>78379c9e7d7e96ed</td>\n",
       "      <td>103.88277</td>\n",
       "      <td>30.91357</td>\n",
       "      <td>103.88685</td>\n",
       "      <td>30.91775</td>\n",
       "      <td>103.88479</td>\n",
       "      <td>30.92339</td>\n",
       "      <td>103.87865</td>\n",
       "      <td>30.92485</td>\n",
       "      <td>103.87457</td>\n",
       "      <td>30.92067</td>\n",
       "      <td>103.87663</td>\n",
       "      <td>30.91503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8496</th>\n",
       "      <td>c721edae074c2faf</td>\n",
       "      <td>103.65947</td>\n",
       "      <td>30.66859</td>\n",
       "      <td>103.66351</td>\n",
       "      <td>30.67275</td>\n",
       "      <td>103.66146</td>\n",
       "      <td>30.67838</td>\n",
       "      <td>103.65535</td>\n",
       "      <td>30.67983</td>\n",
       "      <td>103.65131</td>\n",
       "      <td>30.67567</td>\n",
       "      <td>103.65337</td>\n",
       "      <td>30.67004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8497</th>\n",
       "      <td>8fbd7aa0db599a66</td>\n",
       "      <td>104.50276</td>\n",
       "      <td>30.90925</td>\n",
       "      <td>104.50691</td>\n",
       "      <td>30.91343</td>\n",
       "      <td>104.50488</td>\n",
       "      <td>30.91911</td>\n",
       "      <td>104.49871</td>\n",
       "      <td>30.92060</td>\n",
       "      <td>104.49456</td>\n",
       "      <td>30.91642</td>\n",
       "      <td>104.49658</td>\n",
       "      <td>30.91075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8498</th>\n",
       "      <td>9e50a1332f72f9ab</td>\n",
       "      <td>104.11775</td>\n",
       "      <td>30.46542</td>\n",
       "      <td>104.12184</td>\n",
       "      <td>30.46958</td>\n",
       "      <td>104.11980</td>\n",
       "      <td>30.47523</td>\n",
       "      <td>104.11369</td>\n",
       "      <td>30.47672</td>\n",
       "      <td>104.10961</td>\n",
       "      <td>30.47256</td>\n",
       "      <td>104.11164</td>\n",
       "      <td>30.46691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8499</th>\n",
       "      <td>fb4550d9b69f92e2</td>\n",
       "      <td>103.85797</td>\n",
       "      <td>31.02766</td>\n",
       "      <td>103.86206</td>\n",
       "      <td>31.03184</td>\n",
       "      <td>103.86000</td>\n",
       "      <td>31.03749</td>\n",
       "      <td>103.85385</td>\n",
       "      <td>31.03894</td>\n",
       "      <td>103.84977</td>\n",
       "      <td>31.03476</td>\n",
       "      <td>103.85183</td>\n",
       "      <td>31.02911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8500</th>\n",
       "      <td>16074b906ada179b</td>\n",
       "      <td>104.00368</td>\n",
       "      <td>30.42629</td>\n",
       "      <td>104.00775</td>\n",
       "      <td>30.43044</td>\n",
       "      <td>104.00571</td>\n",
       "      <td>30.43608</td>\n",
       "      <td>103.99961</td>\n",
       "      <td>30.43757</td>\n",
       "      <td>103.99554</td>\n",
       "      <td>30.43341</td>\n",
       "      <td>103.99758</td>\n",
       "      <td>30.42777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8501</th>\n",
       "      <td>a63d2fd0d71498a6</td>\n",
       "      <td>104.12185</td>\n",
       "      <td>30.48503</td>\n",
       "      <td>104.12594</td>\n",
       "      <td>30.48919</td>\n",
       "      <td>104.12391</td>\n",
       "      <td>30.49483</td>\n",
       "      <td>104.11779</td>\n",
       "      <td>30.49632</td>\n",
       "      <td>104.11370</td>\n",
       "      <td>30.49217</td>\n",
       "      <td>104.11574</td>\n",
       "      <td>30.48652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8502</th>\n",
       "      <td>725aa94788c171a6</td>\n",
       "      <td>103.66918</td>\n",
       "      <td>30.33803</td>\n",
       "      <td>103.67321</td>\n",
       "      <td>30.34218</td>\n",
       "      <td>103.67116</td>\n",
       "      <td>30.34780</td>\n",
       "      <td>103.66508</td>\n",
       "      <td>30.34927</td>\n",
       "      <td>103.66106</td>\n",
       "      <td>30.34511</td>\n",
       "      <td>103.66311</td>\n",
       "      <td>30.33950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8503</th>\n",
       "      <td>5b6eca593a79bc18</td>\n",
       "      <td>104.01179</td>\n",
       "      <td>30.51179</td>\n",
       "      <td>104.01587</td>\n",
       "      <td>30.51595</td>\n",
       "      <td>104.01383</td>\n",
       "      <td>30.52159</td>\n",
       "      <td>104.00772</td>\n",
       "      <td>30.52307</td>\n",
       "      <td>104.00364</td>\n",
       "      <td>30.51892</td>\n",
       "      <td>104.00568</td>\n",
       "      <td>30.51327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8504</th>\n",
       "      <td>1b29d93e4279c2c9</td>\n",
       "      <td>103.97516</td>\n",
       "      <td>30.47437</td>\n",
       "      <td>103.97923</td>\n",
       "      <td>30.47853</td>\n",
       "      <td>103.97719</td>\n",
       "      <td>30.48417</td>\n",
       "      <td>103.97108</td>\n",
       "      <td>30.48565</td>\n",
       "      <td>103.96702</td>\n",
       "      <td>30.48149</td>\n",
       "      <td>103.96906</td>\n",
       "      <td>30.47585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8505</th>\n",
       "      <td>8b09e16421b898c2</td>\n",
       "      <td>104.23088</td>\n",
       "      <td>30.81976</td>\n",
       "      <td>104.23500</td>\n",
       "      <td>30.82394</td>\n",
       "      <td>104.23296</td>\n",
       "      <td>30.82960</td>\n",
       "      <td>104.22681</td>\n",
       "      <td>30.83108</td>\n",
       "      <td>104.22270</td>\n",
       "      <td>30.82691</td>\n",
       "      <td>104.22473</td>\n",
       "      <td>30.82125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8506</th>\n",
       "      <td>4f78323469c52960</td>\n",
       "      <td>104.23492</td>\n",
       "      <td>30.79295</td>\n",
       "      <td>104.23903</td>\n",
       "      <td>30.79713</td>\n",
       "      <td>104.23700</td>\n",
       "      <td>30.80279</td>\n",
       "      <td>104.23085</td>\n",
       "      <td>30.80427</td>\n",
       "      <td>104.22673</td>\n",
       "      <td>30.80010</td>\n",
       "      <td>104.22877</td>\n",
       "      <td>30.79444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8507</th>\n",
       "      <td>afd46ac973b45935</td>\n",
       "      <td>103.71837</td>\n",
       "      <td>30.67504</td>\n",
       "      <td>103.72242</td>\n",
       "      <td>30.67921</td>\n",
       "      <td>103.72037</td>\n",
       "      <td>30.68484</td>\n",
       "      <td>103.71426</td>\n",
       "      <td>30.68630</td>\n",
       "      <td>103.71021</td>\n",
       "      <td>30.68213</td>\n",
       "      <td>103.71227</td>\n",
       "      <td>30.67650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8508</th>\n",
       "      <td>b9f15b516e9e8ebb</td>\n",
       "      <td>104.30790</td>\n",
       "      <td>30.54279</td>\n",
       "      <td>104.31201</td>\n",
       "      <td>30.54695</td>\n",
       "      <td>104.30999</td>\n",
       "      <td>30.55261</td>\n",
       "      <td>104.30385</td>\n",
       "      <td>30.55411</td>\n",
       "      <td>104.29974</td>\n",
       "      <td>30.54995</td>\n",
       "      <td>104.30177</td>\n",
       "      <td>30.54429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8509</th>\n",
       "      <td>ae63852b134971de</td>\n",
       "      <td>104.00976</td>\n",
       "      <td>30.50199</td>\n",
       "      <td>104.01383</td>\n",
       "      <td>30.50615</td>\n",
       "      <td>104.01179</td>\n",
       "      <td>30.51179</td>\n",
       "      <td>104.00568</td>\n",
       "      <td>30.51327</td>\n",
       "      <td>104.00161</td>\n",
       "      <td>30.50912</td>\n",
       "      <td>104.00365</td>\n",
       "      <td>30.50347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8510</th>\n",
       "      <td>1439779a8d4283eb</td>\n",
       "      <td>103.72927</td>\n",
       "      <td>30.49274</td>\n",
       "      <td>103.73331</td>\n",
       "      <td>30.49689</td>\n",
       "      <td>103.73126</td>\n",
       "      <td>30.50252</td>\n",
       "      <td>103.72517</td>\n",
       "      <td>30.50399</td>\n",
       "      <td>103.72113</td>\n",
       "      <td>30.49983</td>\n",
       "      <td>103.72318</td>\n",
       "      <td>30.49420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8511</th>\n",
       "      <td>d90076364552bf47</td>\n",
       "      <td>103.64875</td>\n",
       "      <td>30.37883</td>\n",
       "      <td>103.65278</td>\n",
       "      <td>30.38298</td>\n",
       "      <td>103.65073</td>\n",
       "      <td>30.38860</td>\n",
       "      <td>103.64465</td>\n",
       "      <td>30.39007</td>\n",
       "      <td>103.64063</td>\n",
       "      <td>30.38592</td>\n",
       "      <td>103.64268</td>\n",
       "      <td>30.38030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8512</th>\n",
       "      <td>910abf3442e33c57</td>\n",
       "      <td>103.57389</td>\n",
       "      <td>30.38664</td>\n",
       "      <td>103.57791</td>\n",
       "      <td>30.39079</td>\n",
       "      <td>103.57585</td>\n",
       "      <td>30.39641</td>\n",
       "      <td>103.56978</td>\n",
       "      <td>30.39787</td>\n",
       "      <td>103.56576</td>\n",
       "      <td>30.39372</td>\n",
       "      <td>103.56782</td>\n",
       "      <td>30.38810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8513</th>\n",
       "      <td>989711f34a140e4e</td>\n",
       "      <td>104.24556</td>\n",
       "      <td>30.93512</td>\n",
       "      <td>104.24969</td>\n",
       "      <td>30.93930</td>\n",
       "      <td>104.24765</td>\n",
       "      <td>30.94496</td>\n",
       "      <td>104.24148</td>\n",
       "      <td>30.94644</td>\n",
       "      <td>104.23736</td>\n",
       "      <td>30.94226</td>\n",
       "      <td>104.23940</td>\n",
       "      <td>30.93660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8514</th>\n",
       "      <td>b6ce6b8485c72a1b</td>\n",
       "      <td>103.89964</td>\n",
       "      <td>30.62124</td>\n",
       "      <td>103.90371</td>\n",
       "      <td>30.62540</td>\n",
       "      <td>103.90166</td>\n",
       "      <td>30.63104</td>\n",
       "      <td>103.89555</td>\n",
       "      <td>30.63251</td>\n",
       "      <td>103.89148</td>\n",
       "      <td>30.62835</td>\n",
       "      <td>103.89353</td>\n",
       "      <td>30.62271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8515</th>\n",
       "      <td>993596d6f0d5b72d</td>\n",
       "      <td>104.63822</td>\n",
       "      <td>30.81406</td>\n",
       "      <td>104.64238</td>\n",
       "      <td>30.81823</td>\n",
       "      <td>104.64036</td>\n",
       "      <td>30.82391</td>\n",
       "      <td>104.63418</td>\n",
       "      <td>30.82542</td>\n",
       "      <td>104.63002</td>\n",
       "      <td>30.82125</td>\n",
       "      <td>104.63204</td>\n",
       "      <td>30.81557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8516</th>\n",
       "      <td>e694e56895335111</td>\n",
       "      <td>103.98695</td>\n",
       "      <td>31.13636</td>\n",
       "      <td>103.99105</td>\n",
       "      <td>31.14055</td>\n",
       "      <td>103.98900</td>\n",
       "      <td>31.14620</td>\n",
       "      <td>103.98284</td>\n",
       "      <td>31.14766</td>\n",
       "      <td>103.97873</td>\n",
       "      <td>31.14347</td>\n",
       "      <td>103.98079</td>\n",
       "      <td>31.13782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8517</th>\n",
       "      <td>6339eaff3f1ee187</td>\n",
       "      <td>104.10543</td>\n",
       "      <td>30.36029</td>\n",
       "      <td>104.10950</td>\n",
       "      <td>30.36444</td>\n",
       "      <td>104.10747</td>\n",
       "      <td>30.37009</td>\n",
       "      <td>104.10137</td>\n",
       "      <td>30.37158</td>\n",
       "      <td>104.09729</td>\n",
       "      <td>30.36743</td>\n",
       "      <td>104.09932</td>\n",
       "      <td>30.36179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8518</th>\n",
       "      <td>eae23a121eb2ba7b</td>\n",
       "      <td>103.87929</td>\n",
       "      <td>30.61586</td>\n",
       "      <td>103.88335</td>\n",
       "      <td>30.62002</td>\n",
       "      <td>103.88131</td>\n",
       "      <td>30.62566</td>\n",
       "      <td>103.87519</td>\n",
       "      <td>30.62713</td>\n",
       "      <td>103.87113</td>\n",
       "      <td>30.62296</td>\n",
       "      <td>103.87318</td>\n",
       "      <td>30.61733</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8518 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Grid_id     v1_lng    v1_lat     v2_lng    v2_lat     v3_lng  \\\n",
       "0     c151c79af5585f6a  104.46545  30.87166  104.46959  30.87584  104.46756   \n",
       "1     3a1ce6f60c8696eb  103.60379  30.82045  103.60784  30.82462  103.60577   \n",
       "2     aada8f5ae067d90a  104.17495  30.50817  104.17904  30.51233  104.17701   \n",
       "3     4375f4117407765f  103.66009  30.95611  103.66415  30.96029  103.66208   \n",
       "4     2bc0e4d5556e7b48  104.00960  30.96582  104.01370  30.97000  104.01164   \n",
       "5     ace3bb4a658ef318  104.63357  30.74776  104.63773  30.75193  104.63571   \n",
       "6     e3c98397598c1c76  103.98500  30.98716  103.98909  30.99134  103.98704   \n",
       "7     ae1f2fa6c175a64a  103.90827  30.33643  103.91232  30.34058  103.91028   \n",
       "8     dcee410b6fe3282e  103.44397  30.21340  103.44797  30.21755  103.44591   \n",
       "9     5271bff5de1ffc6e  104.13052  30.89558  104.13463  30.89976  104.13258   \n",
       "10    23ab47ea30b86a2e  104.00961  30.91938  104.01371  30.92356  104.01166   \n",
       "11    efab0dee4b2e5d4b  104.05878  30.92310  104.06288  30.92728  104.06084   \n",
       "12    d5905a7da4f635ce  103.55088  30.50996  103.55490  30.51412  103.55284   \n",
       "13    4041553b7ed092e6  103.81641  30.54362  103.82046  30.54778  103.81841   \n",
       "14    f1b6c8117696673e  103.53234  30.56051  103.53636  30.56467  103.53430   \n",
       "15    7e9ff7da4f408d2e  103.59068  30.28020  103.59469  30.28435  103.59264   \n",
       "16    e8c28e64215c5e9c  103.94641  30.70777  103.95048  30.71194  103.94843   \n",
       "17    04f385c0c65f3215  104.06694  30.82311  104.07104  30.82728  104.06899   \n",
       "18    e12ab567c78183b0  103.54363  30.37857  103.54765  30.38272  103.54559   \n",
       "19    80a4533cbfb9b099  103.87344  30.49388  103.87750  30.49804  103.87545   \n",
       "20    9358fc61e324214c  103.77518  30.71797  103.77923  30.72214  103.77718   \n",
       "21    0fce32b720c091ba  104.10786  30.78747  104.11196  30.79164  104.10992   \n",
       "22    11e8bf5e1126df77  104.05455  30.34700  104.05862  30.35115  104.05658   \n",
       "23    46d449c158d95069  104.70591  30.76636  104.71008  30.77053  104.70806   \n",
       "24    5d9a1dd89fb6fa1e  103.76949  30.59601  103.77355  30.60017  103.77149   \n",
       "25    7f0d5628a0368424  104.53587  30.61106  104.54000  30.61523  104.53799   \n",
       "26    ce3c8255c6db1c58  103.97325  30.32572  103.97731  30.32987  103.97527   \n",
       "27    c6f4de53556ead29  103.95826  31.09155  103.96236  31.09574  103.96030   \n",
       "28    42453274fd5765cf  103.86901  30.65948  103.87308  30.66364  103.87103   \n",
       "29    f44d5e1b125f00d4  104.41532  30.72851  104.41945  30.73268  104.41742   \n",
       "...                ...        ...       ...        ...       ...        ...   \n",
       "8489  277fc8734f3b2275  104.30071  30.82874  104.30483  30.83291  104.30279   \n",
       "8490  90f57efc5a53dedc  103.96234  31.11122  103.96644  31.11541  103.96438   \n",
       "8491  863d22e913a49b9c  104.11370  30.49217  104.11779  30.49632  104.11575   \n",
       "8492  1c81beefb29ff1d4  104.33066  30.60438  104.33477  30.60854  104.33274   \n",
       "8493  9ddd02e4ffe66799  103.41965  30.23460  103.42365  30.23874  103.42159   \n",
       "8494  49e984f65860bbc4  104.61257  30.69587  104.61672  30.70003  104.61471   \n",
       "8495  78379c9e7d7e96ed  103.88277  30.91357  103.88685  30.91775  103.88479   \n",
       "8496  c721edae074c2faf  103.65947  30.66859  103.66351  30.67275  103.66146   \n",
       "8497  8fbd7aa0db599a66  104.50276  30.90925  104.50691  30.91343  104.50488   \n",
       "8498  9e50a1332f72f9ab  104.11775  30.46542  104.12184  30.46958  104.11980   \n",
       "8499  fb4550d9b69f92e2  103.85797  31.02766  103.86206  31.03184  103.86000   \n",
       "8500  16074b906ada179b  104.00368  30.42629  104.00775  30.43044  104.00571   \n",
       "8501  a63d2fd0d71498a6  104.12185  30.48503  104.12594  30.48919  104.12391   \n",
       "8502  725aa94788c171a6  103.66918  30.33803  103.67321  30.34218  103.67116   \n",
       "8503  5b6eca593a79bc18  104.01179  30.51179  104.01587  30.51595  104.01383   \n",
       "8504  1b29d93e4279c2c9  103.97516  30.47437  103.97923  30.47853  103.97719   \n",
       "8505  8b09e16421b898c2  104.23088  30.81976  104.23500  30.82394  104.23296   \n",
       "8506  4f78323469c52960  104.23492  30.79295  104.23903  30.79713  104.23700   \n",
       "8507  afd46ac973b45935  103.71837  30.67504  103.72242  30.67921  103.72037   \n",
       "8508  b9f15b516e9e8ebb  104.30790  30.54279  104.31201  30.54695  104.30999   \n",
       "8509  ae63852b134971de  104.00976  30.50199  104.01383  30.50615  104.01179   \n",
       "8510  1439779a8d4283eb  103.72927  30.49274  103.73331  30.49689  103.73126   \n",
       "8511  d90076364552bf47  103.64875  30.37883  103.65278  30.38298  103.65073   \n",
       "8512  910abf3442e33c57  103.57389  30.38664  103.57791  30.39079  103.57585   \n",
       "8513  989711f34a140e4e  104.24556  30.93512  104.24969  30.93930  104.24765   \n",
       "8514  b6ce6b8485c72a1b  103.89964  30.62124  103.90371  30.62540  103.90166   \n",
       "8515  993596d6f0d5b72d  104.63822  30.81406  104.64238  30.81823  104.64036   \n",
       "8516  e694e56895335111  103.98695  31.13636  103.99105  31.14055  103.98900   \n",
       "8517  6339eaff3f1ee187  104.10543  30.36029  104.10950  30.36444  104.10747   \n",
       "8518  eae23a121eb2ba7b  103.87929  30.61586  103.88335  30.62002  103.88131   \n",
       "\n",
       "        v3_lat     v4_lng    v4_lat     v5_lng    v5_lat     v6_lng    v6_lat  \n",
       "0     30.88151  104.46139  30.88301  104.45725  30.87883  104.45927  30.87316  \n",
       "1     30.83025  103.59966  30.83170  103.59562  30.82752  103.59769  30.82190  \n",
       "2     30.51798  104.17088  30.51947  104.16679  30.51531  104.16882  30.50966  \n",
       "3     30.96592  103.65596  30.96737  103.65190  30.96319  103.65397  30.95756  \n",
       "4     30.97565  104.00550  30.97711  104.00140  30.97293  104.00345  30.96728  \n",
       "5     30.75761  104.62954  30.75912  104.62538  30.75495  104.62740  30.74927  \n",
       "6     30.99699  103.98089  30.99845  103.97680  30.99427  103.97885  30.98862  \n",
       "7     30.34621  103.90419  30.34769  103.90014  30.34354  103.90218  30.33791  \n",
       "8     30.22315  103.43986  30.22461  103.43587  30.22047  103.43793  30.21486  \n",
       "9     30.90541  104.12643  30.90689  104.12232  30.90271  104.12437  30.89706  \n",
       "10    30.92921  104.00551  30.93068  104.00142  30.92650  104.00347  30.92085  \n",
       "11    30.93293  104.05469  30.93440  104.05059  30.93022  104.05264  30.92457  \n",
       "12    30.51974  103.54676  30.52120  103.54274  30.51704  103.54480  30.51142  \n",
       "13    30.55341  103.81231  30.55489  103.80826  30.55072  103.81030  30.54509  \n",
       "14    30.57029  103.52821  30.57174  103.52419  30.56758  103.52625  30.56196  \n",
       "15    30.28996  103.58658  30.29143  103.58256  30.28728  103.58462  30.28167  \n",
       "16    30.71758  103.94231  30.71905  103.93823  30.71488  103.94028  30.70924  \n",
       "17    30.83293  104.06285  30.83441  104.05876  30.83023  104.06080  30.82458  \n",
       "18    30.38833  103.53952  30.38980  103.53551  30.38564  103.53756  30.38003  \n",
       "19    30.50367  103.86935  30.50515  103.86529  30.50099  103.86734  30.49536  \n",
       "20    30.72778  103.77107  30.72924  103.76701  30.72507  103.76906  30.71944  \n",
       "21    30.79729  104.10378  30.79877  104.09968  30.79460  104.10172  30.78895  \n",
       "22    30.35680  104.05048  30.35829  104.04641  30.35414  104.04845  30.34849  \n",
       "23    30.77621  104.70189  30.77773  104.69772  30.77356  104.69974  30.76787  \n",
       "24    30.60580  103.76539  30.60727  103.76134  30.60311  103.76339  30.59748  \n",
       "25    30.62090  104.53183  30.62241  104.52769  30.61825  104.52971  30.61257  \n",
       "26    30.33551  103.96918  30.33699  103.96512  30.33285  103.96716  30.32721  \n",
       "27    31.10138  103.95414  31.10284  103.95005  31.09865  103.95210  31.09301  \n",
       "28    30.66928  103.86492  30.67075  103.86085  30.66658  103.86290  30.66094  \n",
       "29    30.73835  104.41127  30.73985  104.40714  30.73568  104.40916  30.73001  \n",
       "...        ...        ...       ...        ...       ...        ...       ...  \n",
       "8489  30.83858  104.29664  30.84007  104.29251  30.83589  104.29455  30.83023  \n",
       "8490  31.12106  103.95823  31.12252  103.95413  31.11833  103.95619  31.11268  \n",
       "8491  30.50197  104.10964  30.50346  104.10555  30.49930  104.10759  30.49366  \n",
       "8492  30.61420  104.32660  30.61570  104.32249  30.61154  104.32452  30.60588  \n",
       "8493  30.24435  103.41554  30.24580  103.41155  30.24166  103.41360  30.23605  \n",
       "8494  30.70571  104.60854  30.70722  104.60439  30.70306  104.60641  30.69738  \n",
       "8495  30.92339  103.87865  30.92485  103.87457  30.92067  103.87663  30.91503  \n",
       "8496  30.67838  103.65535  30.67983  103.65131  30.67567  103.65337  30.67004  \n",
       "8497  30.91911  104.49871  30.92060  104.49456  30.91642  104.49658  30.91075  \n",
       "8498  30.47523  104.11369  30.47672  104.10961  30.47256  104.11164  30.46691  \n",
       "8499  31.03749  103.85385  31.03894  103.84977  31.03476  103.85183  31.02911  \n",
       "8500  30.43608  103.99961  30.43757  103.99554  30.43341  103.99758  30.42777  \n",
       "8501  30.49483  104.11779  30.49632  104.11370  30.49217  104.11574  30.48652  \n",
       "8502  30.34780  103.66508  30.34927  103.66106  30.34511  103.66311  30.33950  \n",
       "8503  30.52159  104.00772  30.52307  104.00364  30.51892  104.00568  30.51327  \n",
       "8504  30.48417  103.97108  30.48565  103.96702  30.48149  103.96906  30.47585  \n",
       "8505  30.82960  104.22681  30.83108  104.22270  30.82691  104.22473  30.82125  \n",
       "8506  30.80279  104.23085  30.80427  104.22673  30.80010  104.22877  30.79444  \n",
       "8507  30.68484  103.71426  30.68630  103.71021  30.68213  103.71227  30.67650  \n",
       "8508  30.55261  104.30385  30.55411  104.29974  30.54995  104.30177  30.54429  \n",
       "8509  30.51179  104.00568  30.51327  104.00161  30.50912  104.00365  30.50347  \n",
       "8510  30.50252  103.72517  30.50399  103.72113  30.49983  103.72318  30.49420  \n",
       "8511  30.38860  103.64465  30.39007  103.64063  30.38592  103.64268  30.38030  \n",
       "8512  30.39641  103.56978  30.39787  103.56576  30.39372  103.56782  30.38810  \n",
       "8513  30.94496  104.24148  30.94644  104.23736  30.94226  104.23940  30.93660  \n",
       "8514  30.63104  103.89555  30.63251  103.89148  30.62835  103.89353  30.62271  \n",
       "8515  30.82391  104.63418  30.82542  104.63002  30.82125  104.63204  30.81557  \n",
       "8516  31.14620  103.98284  31.14766  103.97873  31.14347  103.98079  31.13782  \n",
       "8517  30.37009  104.10137  30.37158  104.09729  30.36743  104.09932  30.36179  \n",
       "8518  30.62566  103.87519  30.62713  103.87113  30.62296  103.87318  30.61733  \n",
       "\n",
       "[8518 rows x 13 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Grid_range=pd.read_csv('./Experiments/Demo/hexagon_grid_table.csv',header=None,\n",
    "                            names = ['Grid_id','v1_lng','v1_lat',\\\n",
    "                                    'v2_lng','v2_lat',\\\n",
    "                                    'v3_lng','v3_lat',\\\n",
    "                                    'v4_lng','v4_lat',\\\n",
    "                                    'v5_lng','v5_lat',\\\n",
    "                                    'v6_lng','v6_lat'])\n",
    "\n",
    "Grid_range=Grid_range.dropna(subset=['v1_lng','v1_lat',\\\n",
    "                                    'v2_lng','v2_lat',\\\n",
    "                                    'v3_lng','v3_lat',\\\n",
    "                                    'v4_lng','v4_lat',\\\n",
    "                                    'v5_lng','v5_lat',\\\n",
    "                                    'v6_lng','v6_lat'])\n",
    "\n",
    "Grid_range\n",
    "\n",
    "# X=list(Grid_range['v1_lng'])+list(Grid_range['v2_lng'])+list(Grid_range['v3_lng'])\\\n",
    "#     +list(Grid_range['v4_lng'])+list(Grid_range['v5_lng'])+list(Grid_range['v6_lng'])\n",
    "\n",
    "# Y=list(Grid_range['v1_lat'])+list(Grid_range['v2_lat'])+list(Grid_range['v3_lat'])\\\n",
    "#     +list(Grid_range['v4_lat'])+list(Grid_range['v5_lat'])+list(Grid_range['v6_lat'])\n",
    "\n",
    "# print(min(X),min(Y))\n",
    "\n",
    "# print(max(X),max(Y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Order Transition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Order_id</th>\n",
       "      <th>Start_step</th>\n",
       "      <th>Stop_step</th>\n",
       "      <th>Start_grid</th>\n",
       "      <th>Stop_grid</th>\n",
       "      <th>Reward_unit</th>\n",
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       "      <th>59</th>\n",
       "      <td>2cdab7b0f6b8ea423fb64379924c8794</td>\n",
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       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>f56808dd28a80a4352a9dac6845ec83d</td>\n",
       "      <td>93</td>\n",
       "      <td>107</td>\n",
       "      <td>2734</td>\n",
       "      <td>1</td>\n",
       "      <td>25.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>1591ccc6f15e7aca4bcc8c83fdee582b</td>\n",
       "      <td>164</td>\n",
       "      <td>186</td>\n",
       "      <td>2478</td>\n",
       "      <td>49</td>\n",
       "      <td>31.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>8e419fe703934fe50d7c8503952790e9</td>\n",
       "      <td>189</td>\n",
       "      <td>209</td>\n",
       "      <td>2383</td>\n",
       "      <td>49</td>\n",
       "      <td>30.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>5e097419d2e29185654c22dbc52febac</td>\n",
       "      <td>34</td>\n",
       "      <td>45</td>\n",
       "      <td>2383</td>\n",
       "      <td>290</td>\n",
       "      <td>24.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>cf29e2b4873361534a10891c650e9cde</td>\n",
       "      <td>284</td>\n",
       "      <td>305</td>\n",
       "      <td>2478</td>\n",
       "      <td>267</td>\n",
       "      <td>33.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>5de1b3604011fa52471941501ff8ad78</td>\n",
       "      <td>231</td>\n",
       "      <td>244</td>\n",
       "      <td>2437</td>\n",
       "      <td>280</td>\n",
       "      <td>21.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2d0a863aa14b4e5f69daf4605a456de3</td>\n",
       "      <td>211</td>\n",
       "      <td>217</td>\n",
       "      <td>2722</td>\n",
       "      <td>351</td>\n",
       "      <td>1.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>d20263896a9f3d89bb020cfa597642f8</td>\n",
       "      <td>147</td>\n",
       "      <td>162</td>\n",
       "      <td>2478</td>\n",
       "      <td>338</td>\n",
       "      <td>22.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>f691248b8baee33bd29845669c403191</td>\n",
       "      <td>153</td>\n",
       "      <td>171</td>\n",
       "      <td>2409</td>\n",
       "      <td>380</td>\n",
       "      <td>20.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>ba0a3133af383e6d93f746cfaa12b5d1</td>\n",
       "      <td>247</td>\n",
       "      <td>247</td>\n",
       "      <td>2586</td>\n",
       "      <td>430</td>\n",
       "      <td>1.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>f2debe86bfdf7930eefc051612001de8</td>\n",
       "      <td>251</td>\n",
       "      <td>267</td>\n",
       "      <td>2586</td>\n",
       "      <td>430</td>\n",
       "      <td>26.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>0744d080438cf125fcce96ec3029c792</td>\n",
       "      <td>210</td>\n",
       "      <td>221</td>\n",
       "      <td>2342</td>\n",
       "      <td>465</td>\n",
       "      <td>16.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>a5d9707bba2b2477a9a56a2f07e3e8ca</td>\n",
       "      <td>273</td>\n",
       "      <td>273</td>\n",
       "      <td>2478</td>\n",
       "      <td>465</td>\n",
       "      <td>1.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>e6a5d748610549a8a914ac2cfe9b7b29</td>\n",
       "      <td>128</td>\n",
       "      <td>140</td>\n",
       "      <td>2708</td>\n",
       "      <td>465</td>\n",
       "      <td>20.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>f0a4160d2443d069bf475252b5a70531</td>\n",
       "      <td>117</td>\n",
       "      <td>117</td>\n",
       "      <td>2708</td>\n",
       "      <td>465</td>\n",
       "      <td>2.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>f9dd261ae590e8635c789a8c7eef64fb</td>\n",
       "      <td>227</td>\n",
       "      <td>237</td>\n",
       "      <td>2478</td>\n",
       "      <td>449</td>\n",
       "      <td>16.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>8db065f4b75dceb6c5ccc76f5e68033f</td>\n",
       "      <td>198</td>\n",
       "      <td>210</td>\n",
       "      <td>2505</td>\n",
       "      <td>449</td>\n",
       "      <td>17.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>465618f696a3184d9d6b3da967268889</td>\n",
       "      <td>195</td>\n",
       "      <td>195</td>\n",
       "      <td>2505</td>\n",
       "      <td>449</td>\n",
       "      <td>1.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>dd770083b6d33f54f84f5ac2877e3157</td>\n",
       "      <td>140</td>\n",
       "      <td>149</td>\n",
       "      <td>2546</td>\n",
       "      <td>465</td>\n",
       "      <td>15.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>eecc486447df43f0b63efb14e609d371</td>\n",
       "      <td>182</td>\n",
       "      <td>191</td>\n",
       "      <td>2451</td>\n",
       "      <td>516</td>\n",
       "      <td>15.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>ac5a92b3be8fd5415006a1e8d1abf2d6</td>\n",
       "      <td>215</td>\n",
       "      <td>217</td>\n",
       "      <td>2532</td>\n",
       "      <td>481</td>\n",
       "      <td>1.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>ae00c2a980b1effc341126492eda5c06</td>\n",
       "      <td>196</td>\n",
       "      <td>207</td>\n",
       "      <td>3041</td>\n",
       "      <td>479</td>\n",
       "      <td>23.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>78bbd08ae1bbe9b9f88240c61d8b2bae</td>\n",
       "      <td>258</td>\n",
       "      <td>272</td>\n",
       "      <td>2478</td>\n",
       "      <td>493</td>\n",
       "      <td>21.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0bdbf03a67df13e8c210daa35d90fc81</td>\n",
       "      <td>158</td>\n",
       "      <td>167</td>\n",
       "      <td>2695</td>\n",
       "      <td>517</td>\n",
       "      <td>18.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0e87f6f327eba0befbcc17c6c5527b2f</td>\n",
       "      <td>138</td>\n",
       "      <td>149</td>\n",
       "      <td>2491</td>\n",
       "      <td>504</td>\n",
       "      <td>16.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>7bbd52e3ac540c6f7bc932d8effd1b15</td>\n",
       "      <td>231</td>\n",
       "      <td>231</td>\n",
       "      <td>2627</td>\n",
       "      <td>555</td>\n",
       "      <td>1.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>b888e19a57c3f82cbb9753205a20eedb</td>\n",
       "      <td>209</td>\n",
       "      <td>213</td>\n",
       "      <td>2492</td>\n",
       "      <td>572</td>\n",
       "      <td>2.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>df50c4def567cc428f08d5200f5b8d7f</td>\n",
       "      <td>113</td>\n",
       "      <td>132</td>\n",
       "      <td>3175</td>\n",
       "      <td>548</td>\n",
       "      <td>28.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>f206885d93334899e557ea170a1ee949</td>\n",
       "      <td>189</td>\n",
       "      <td>210</td>\n",
       "      <td>2491</td>\n",
       "      <td>602</td>\n",
       "      <td>20.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209334</th>\n",
       "      <td>5b55b87aaaaecd8b9cbe55edab7cd1a6</td>\n",
       "      <td>28</td>\n",
       "      <td>35</td>\n",
       "      <td>2680</td>\n",
       "      <td>3763</td>\n",
       "      <td>15.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209335</th>\n",
       "      <td>0e3fa9d72b33a751865b537db8a48153</td>\n",
       "      <td>70</td>\n",
       "      <td>76</td>\n",
       "      <td>2626</td>\n",
       "      <td>3773</td>\n",
       "      <td>15.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209336</th>\n",
       "      <td>9887d51324955353e182be05aafa348a</td>\n",
       "      <td>229</td>\n",
       "      <td>237</td>\n",
       "      <td>2491</td>\n",
       "      <td>3773</td>\n",
       "      <td>11.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209337</th>\n",
       "      <td>585cdc8d9abdef7e5c88d606f922c5e6</td>\n",
       "      <td>93</td>\n",
       "      <td>100</td>\n",
       "      <td>2208</td>\n",
       "      <td>3773</td>\n",
       "      <td>14.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209339</th>\n",
       "      <td>86dd15483377c27523341ca327e1748b</td>\n",
       "      <td>107</td>\n",
       "      <td>118</td>\n",
       "      <td>2560</td>\n",
       "      <td>3789</td>\n",
       "      <td>16.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209340</th>\n",
       "      <td>e3df67630fb3f71e0b0c4ef4d42df1bc</td>\n",
       "      <td>125</td>\n",
       "      <td>134</td>\n",
       "      <td>2709</td>\n",
       "      <td>3789</td>\n",
       "      <td>13.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209342</th>\n",
       "      <td>a042b46df96f3e8eb7a61692fa669b91</td>\n",
       "      <td>191</td>\n",
       "      <td>201</td>\n",
       "      <td>2437</td>\n",
       "      <td>3819</td>\n",
       "      <td>14.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209343</th>\n",
       "      <td>60f750f378c82506500bde1e307749a4</td>\n",
       "      <td>259</td>\n",
       "      <td>272</td>\n",
       "      <td>2559</td>\n",
       "      <td>3819</td>\n",
       "      <td>14.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209344</th>\n",
       "      <td>6a86d8d2be0ffdd4f7cc4990edbd9a1e</td>\n",
       "      <td>250</td>\n",
       "      <td>256</td>\n",
       "      <td>2829</td>\n",
       "      <td>3819</td>\n",
       "      <td>9.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209347</th>\n",
       "      <td>68673048eabdf17beaf939c35a088c11</td>\n",
       "      <td>142</td>\n",
       "      <td>150</td>\n",
       "      <td>2315</td>\n",
       "      <td>3819</td>\n",
       "      <td>12.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209348</th>\n",
       "      <td>adb6ade6fd1ced684fa4d5262ef61985</td>\n",
       "      <td>130</td>\n",
       "      <td>139</td>\n",
       "      <td>2275</td>\n",
       "      <td>3819</td>\n",
       "      <td>16.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209349</th>\n",
       "      <td>4d88914c4f49cb0dbb4fc776b6fe9cf6</td>\n",
       "      <td>229</td>\n",
       "      <td>243</td>\n",
       "      <td>2383</td>\n",
       "      <td>3819</td>\n",
       "      <td>16.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209351</th>\n",
       "      <td>00a3b9842a460f0acf07fa059e5b08d8</td>\n",
       "      <td>178</td>\n",
       "      <td>191</td>\n",
       "      <td>2478</td>\n",
       "      <td>3810</td>\n",
       "      <td>16.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209352</th>\n",
       "      <td>562b29993ddf2be8f8215abe7a245f58</td>\n",
       "      <td>184</td>\n",
       "      <td>193</td>\n",
       "      <td>2478</td>\n",
       "      <td>3810</td>\n",
       "      <td>14.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209353</th>\n",
       "      <td>fcf16489b6d14a2860cc531ac9b508fe</td>\n",
       "      <td>162</td>\n",
       "      <td>171</td>\n",
       "      <td>2478</td>\n",
       "      <td>3819</td>\n",
       "      <td>14.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209354</th>\n",
       "      <td>ad7fa78185ea0d1ffa696491e4d6b053</td>\n",
       "      <td>214</td>\n",
       "      <td>221</td>\n",
       "      <td>2559</td>\n",
       "      <td>3819</td>\n",
       "      <td>11.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209355</th>\n",
       "      <td>a5df6e773e4af36e315531feea820b15</td>\n",
       "      <td>170</td>\n",
       "      <td>185</td>\n",
       "      <td>2383</td>\n",
       "      <td>3867</td>\n",
       "      <td>17.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209356</th>\n",
       "      <td>9e050c3d8901083ee6afb3e1c26b11b9</td>\n",
       "      <td>197</td>\n",
       "      <td>197</td>\n",
       "      <td>2815</td>\n",
       "      <td>3867</td>\n",
       "      <td>2.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209357</th>\n",
       "      <td>395eb7cc6e5b04250b2dfa4899b7ce4b</td>\n",
       "      <td>14</td>\n",
       "      <td>21</td>\n",
       "      <td>2545</td>\n",
       "      <td>3884</td>\n",
       "      <td>16.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209358</th>\n",
       "      <td>f4e5d5a21f79c46abbb0f40c4a28d5f9</td>\n",
       "      <td>219</td>\n",
       "      <td>229</td>\n",
       "      <td>2613</td>\n",
       "      <td>3889</td>\n",
       "      <td>14.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209359</th>\n",
       "      <td>9336fcfed4d5996e7ed9c6e3dbd2b835</td>\n",
       "      <td>224</td>\n",
       "      <td>235</td>\n",
       "      <td>2478</td>\n",
       "      <td>3898</td>\n",
       "      <td>16.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209360</th>\n",
       "      <td>c8aca248397fb9721a29d597983998e1</td>\n",
       "      <td>23</td>\n",
       "      <td>30</td>\n",
       "      <td>2748</td>\n",
       "      <td>3898</td>\n",
       "      <td>15.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209362</th>\n",
       "      <td>bd8ae86eded16f798acc2f78b53f4648</td>\n",
       "      <td>275</td>\n",
       "      <td>276</td>\n",
       "      <td>2546</td>\n",
       "      <td>3898</td>\n",
       "      <td>1.94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209363</th>\n",
       "      <td>182a627fbae8e49de90371c145c18098</td>\n",
       "      <td>117</td>\n",
       "      <td>135</td>\n",
       "      <td>2108</td>\n",
       "      <td>3898</td>\n",
       "      <td>28.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209364</th>\n",
       "      <td>b61c89fef5eff068dbb465c3da39fce8</td>\n",
       "      <td>185</td>\n",
       "      <td>194</td>\n",
       "      <td>2437</td>\n",
       "      <td>3898</td>\n",
       "      <td>14.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209366</th>\n",
       "      <td>4719e7bd4913f809873fcd5d966d11cf</td>\n",
       "      <td>133</td>\n",
       "      <td>143</td>\n",
       "      <td>2748</td>\n",
       "      <td>3898</td>\n",
       "      <td>13.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209367</th>\n",
       "      <td>e18aa4443ed30e9c5976d7308fdf2115</td>\n",
       "      <td>212</td>\n",
       "      <td>229</td>\n",
       "      <td>2193</td>\n",
       "      <td>3919</td>\n",
       "      <td>23.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209369</th>\n",
       "      <td>7ec5baa07206c9fc6c4305aa479f2288</td>\n",
       "      <td>110</td>\n",
       "      <td>121</td>\n",
       "      <td>1989</td>\n",
       "      <td>3997</td>\n",
       "      <td>20.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209370</th>\n",
       "      <td>daecb57ca9206ad215141062b940403e</td>\n",
       "      <td>13</td>\n",
       "      <td>20</td>\n",
       "      <td>2761</td>\n",
       "      <td>4064</td>\n",
       "      <td>21.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209371</th>\n",
       "      <td>0b562f96dcb9f357ef5470c7db5806d9</td>\n",
       "      <td>126</td>\n",
       "      <td>141</td>\n",
       "      <td>2410</td>\n",
       "      <td>4095</td>\n",
       "      <td>20.45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>181062 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Order_id  Start_step  Stop_step  Start_grid  \\\n",
       "59      2cdab7b0f6b8ea423fb64379924c8794         149        160        2369   \n",
       "61      f56808dd28a80a4352a9dac6845ec83d          93        107        2734   \n",
       "62      1591ccc6f15e7aca4bcc8c83fdee582b         164        186        2478   \n",
       "63      8e419fe703934fe50d7c8503952790e9         189        209        2383   \n",
       "65      5e097419d2e29185654c22dbc52febac          34         45        2383   \n",
       "66      cf29e2b4873361534a10891c650e9cde         284        305        2478   \n",
       "67      5de1b3604011fa52471941501ff8ad78         231        244        2437   \n",
       "68      2d0a863aa14b4e5f69daf4605a456de3         211        217        2722   \n",
       "69      d20263896a9f3d89bb020cfa597642f8         147        162        2478   \n",
       "70      f691248b8baee33bd29845669c403191         153        171        2409   \n",
       "72      ba0a3133af383e6d93f746cfaa12b5d1         247        247        2586   \n",
       "73      f2debe86bfdf7930eefc051612001de8         251        267        2586   \n",
       "74      0744d080438cf125fcce96ec3029c792         210        221        2342   \n",
       "75      a5d9707bba2b2477a9a56a2f07e3e8ca         273        273        2478   \n",
       "76      e6a5d748610549a8a914ac2cfe9b7b29         128        140        2708   \n",
       "77      f0a4160d2443d069bf475252b5a70531         117        117        2708   \n",
       "79      f9dd261ae590e8635c789a8c7eef64fb         227        237        2478   \n",
       "80      8db065f4b75dceb6c5ccc76f5e68033f         198        210        2505   \n",
       "81      465618f696a3184d9d6b3da967268889         195        195        2505   \n",
       "82      dd770083b6d33f54f84f5ac2877e3157         140        149        2546   \n",
       "83      eecc486447df43f0b63efb14e609d371         182        191        2451   \n",
       "85      ac5a92b3be8fd5415006a1e8d1abf2d6         215        217        2532   \n",
       "86      ae00c2a980b1effc341126492eda5c06         196        207        3041   \n",
       "87      78bbd08ae1bbe9b9f88240c61d8b2bae         258        272        2478   \n",
       "88      0bdbf03a67df13e8c210daa35d90fc81         158        167        2695   \n",
       "89      0e87f6f327eba0befbcc17c6c5527b2f         138        149        2491   \n",
       "90      7bbd52e3ac540c6f7bc932d8effd1b15         231        231        2627   \n",
       "91      b888e19a57c3f82cbb9753205a20eedb         209        213        2492   \n",
       "92      df50c4def567cc428f08d5200f5b8d7f         113        132        3175   \n",
       "94      f206885d93334899e557ea170a1ee949         189        210        2491   \n",
       "...                                  ...         ...        ...         ...   \n",
       "209334  5b55b87aaaaecd8b9cbe55edab7cd1a6          28         35        2680   \n",
       "209335  0e3fa9d72b33a751865b537db8a48153          70         76        2626   \n",
       "209336  9887d51324955353e182be05aafa348a         229        237        2491   \n",
       "209337  585cdc8d9abdef7e5c88d606f922c5e6          93        100        2208   \n",
       "209339  86dd15483377c27523341ca327e1748b         107        118        2560   \n",
       "209340  e3df67630fb3f71e0b0c4ef4d42df1bc         125        134        2709   \n",
       "209342  a042b46df96f3e8eb7a61692fa669b91         191        201        2437   \n",
       "209343  60f750f378c82506500bde1e307749a4         259        272        2559   \n",
       "209344  6a86d8d2be0ffdd4f7cc4990edbd9a1e         250        256        2829   \n",
       "209347  68673048eabdf17beaf939c35a088c11         142        150        2315   \n",
       "209348  adb6ade6fd1ced684fa4d5262ef61985         130        139        2275   \n",
       "209349  4d88914c4f49cb0dbb4fc776b6fe9cf6         229        243        2383   \n",
       "209351  00a3b9842a460f0acf07fa059e5b08d8         178        191        2478   \n",
       "209352  562b29993ddf2be8f8215abe7a245f58         184        193        2478   \n",
       "209353  fcf16489b6d14a2860cc531ac9b508fe         162        171        2478   \n",
       "209354  ad7fa78185ea0d1ffa696491e4d6b053         214        221        2559   \n",
       "209355  a5df6e773e4af36e315531feea820b15         170        185        2383   \n",
       "209356  9e050c3d8901083ee6afb3e1c26b11b9         197        197        2815   \n",
       "209357  395eb7cc6e5b04250b2dfa4899b7ce4b          14         21        2545   \n",
       "209358  f4e5d5a21f79c46abbb0f40c4a28d5f9         219        229        2613   \n",
       "209359  9336fcfed4d5996e7ed9c6e3dbd2b835         224        235        2478   \n",
       "209360  c8aca248397fb9721a29d597983998e1          23         30        2748   \n",
       "209362  bd8ae86eded16f798acc2f78b53f4648         275        276        2546   \n",
       "209363  182a627fbae8e49de90371c145c18098         117        135        2108   \n",
       "209364  b61c89fef5eff068dbb465c3da39fce8         185        194        2437   \n",
       "209366  4719e7bd4913f809873fcd5d966d11cf         133        143        2748   \n",
       "209367  e18aa4443ed30e9c5976d7308fdf2115         212        229        2193   \n",
       "209369  7ec5baa07206c9fc6c4305aa479f2288         110        121        1989   \n",
       "209370  daecb57ca9206ad215141062b940403e          13         20        2761   \n",
       "209371  0b562f96dcb9f357ef5470c7db5806d9         126        141        2410   \n",
       "\n",
       "        Stop_grid  Reward_unit  \n",
       "59              1        21.40  \n",
       "61              1        25.10  \n",
       "62             49        31.96  \n",
       "63             49        30.67  \n",
       "65            290        24.94  \n",
       "66            267        33.98  \n",
       "67            280        21.53  \n",
       "68            351         1.81  \n",
       "69            338        22.05  \n",
       "70            380        20.30  \n",
       "72            430         1.97  \n",
       "73            430        26.85  \n",
       "74            465        16.97  \n",
       "75            465         1.99  \n",
       "76            465        20.18  \n",
       "77            465         2.38  \n",
       "79            449        16.53  \n",
       "80            449        17.81  \n",
       "81            449         1.40  \n",
       "82            465        15.26  \n",
       "83            516        15.29  \n",
       "85            481         1.93  \n",
       "86            479        23.19  \n",
       "87            493        21.49  \n",
       "88            517        18.32  \n",
       "89            504        16.57  \n",
       "90            555         1.46  \n",
       "91            572         2.91  \n",
       "92            548        28.21  \n",
       "94            602        20.06  \n",
       "...           ...          ...  \n",
       "209334       3763        15.46  \n",
       "209335       3773        15.94  \n",
       "209336       3773        11.79  \n",
       "209337       3773        14.18  \n",
       "209339       3789        16.73  \n",
       "209340       3789        13.66  \n",
       "209342       3819        14.26  \n",
       "209343       3819        14.57  \n",
       "209344       3819         9.76  \n",
       "209347       3819        12.82  \n",
       "209348       3819        16.47  \n",
       "209349       3819        16.69  \n",
       "209351       3810        16.58  \n",
       "209352       3810        14.86  \n",
       "209353       3819        14.86  \n",
       "209354       3819        11.34  \n",
       "209355       3867        17.88  \n",
       "209356       3867         2.88  \n",
       "209357       3884        16.38  \n",
       "209358       3889        14.22  \n",
       "209359       3898        16.29  \n",
       "209360       3898        15.36  \n",
       "209362       3898         1.94  \n",
       "209363       3898        28.96  \n",
       "209364       3898        14.26  \n",
       "209366       3898        13.63  \n",
       "209367       3919        23.23  \n",
       "209369       3997        20.56  \n",
       "209370       4064        21.27  \n",
       "209371       4095        20.45  \n",
       "\n",
       "[181062 rows x 6 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_str='2016-11-01'\n",
    "\n",
    "OrderTran=pd.read_csv('./Experiments/Demo/OrderTran1101.csv')\n",
    "\n",
    "OrderTran=OrderTran.drop(columns=['Unnamed: 0'])\n",
    "\n",
    "OrderTran.columns = ['Order_id','Start_time','Stop_time','Pickup_Longitude','Pickup_Latitude',\\\n",
    "                                    'Dropoff_Longitude','Dropoff_Latitude','Reward_unit','Start_grid','Stop_grid']\n",
    "\n",
    "OrderTran['Start_step']=OrderTran.apply(lambda x:stamp_to_step(x['Start_time'],date_str,300), axis=1)\n",
    "\n",
    "OrderTran['Stop_step']=OrderTran.apply(lambda x:stamp_to_step(x['Stop_time'],date_str,300), axis=1)\n",
    "\n",
    "OrderTran=OrderTran[['Order_id','Start_step','Stop_step','Start_grid','Stop_grid','Reward_unit']]\n",
    "\n",
    "OrderTran=OrderTran.loc[OrderTran['Stop_grid']!=0]\n",
    "\n",
    "OrderTran=OrderTran.drop_duplicates(subset=['Order_id'], keep='last', inplace=False)\n",
    "\n",
    "OrderTran"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Start_grid</th>\n",
       "      <th>Stop_grid</th>\n",
       "      <th>Order_Cnt</th>\n",
       "      <th>Order_Sum</th>\n",
       "      <th>Prob</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>2111</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>2138</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>2224</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>2234</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>2275</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>2288</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0</td>\n",
       "      <td>2315</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>2383</td>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0</td>\n",
       "      <td>2423</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>2437</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0</td>\n",
       "      <td>2451</td>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>2464</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0</td>\n",
       "      <td>2478</td>\n",
       "      <td>3</td>\n",
       "      <td>27</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>2491</td>\n",
       "      <td>2</td>\n",
       "      <td>27</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0</td>\n",
       "      <td>2505</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0</td>\n",
       "      <td>2519</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0</td>\n",
       "      <td>2545</td>\n",
       "      <td>4</td>\n",
       "      <td>27</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0</td>\n",
       "      <td>2559</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0</td>\n",
       "      <td>2598</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>264</td>\n",
       "      <td>2709</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>328</td>\n",
       "      <td>2722</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>437</td>\n",
       "      <td>2559</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>439</td>\n",
       "      <td>2275</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>504</td>\n",
       "      <td>2491</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>564</td>\n",
       "      <td>2491</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>584</td>\n",
       "      <td>2531</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>584</td>\n",
       "      <td>2559</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>587</td>\n",
       "      <td>2667</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>591</td>\n",
       "      <td>2424</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>610</td>\n",
       "      <td>1797</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47899</th>\n",
       "      <td>3784</td>\n",
       "      <td>2383</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47900</th>\n",
       "      <td>3789</td>\n",
       "      <td>2560</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47901</th>\n",
       "      <td>3803</td>\n",
       "      <td>2694</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47902</th>\n",
       "      <td>3806</td>\n",
       "      <td>2613</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47903</th>\n",
       "      <td>3810</td>\n",
       "      <td>2369</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47904</th>\n",
       "      <td>3810</td>\n",
       "      <td>2641</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47905</th>\n",
       "      <td>3819</td>\n",
       "      <td>2136</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47906</th>\n",
       "      <td>3819</td>\n",
       "      <td>2315</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47907</th>\n",
       "      <td>3819</td>\n",
       "      <td>2478</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47908</th>\n",
       "      <td>3819</td>\n",
       "      <td>2559</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47909</th>\n",
       "      <td>3819</td>\n",
       "      <td>2626</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47910</th>\n",
       "      <td>3819</td>\n",
       "      <td>2681</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47911</th>\n",
       "      <td>3819</td>\n",
       "      <td>2748</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47912</th>\n",
       "      <td>3819</td>\n",
       "      <td>2829</td>\n",
       "      <td>1</td>\n",
       "      <td>8</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47913</th>\n",
       "      <td>3830</td>\n",
       "      <td>2383</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47914</th>\n",
       "      <td>3845</td>\n",
       "      <td>2734</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47915</th>\n",
       "      <td>3849</td>\n",
       "      <td>2640</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47916</th>\n",
       "      <td>3857</td>\n",
       "      <td>2545</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47917</th>\n",
       "      <td>3867</td>\n",
       "      <td>2410</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47918</th>\n",
       "      <td>3867</td>\n",
       "      <td>2680</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47919</th>\n",
       "      <td>3893</td>\n",
       "      <td>2193</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47920</th>\n",
       "      <td>3898</td>\n",
       "      <td>1730</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47921</th>\n",
       "      <td>3898</td>\n",
       "      <td>2043</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47922</th>\n",
       "      <td>3898</td>\n",
       "      <td>2316</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47923</th>\n",
       "      <td>3898</td>\n",
       "      <td>2383</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47924</th>\n",
       "      <td>3898</td>\n",
       "      <td>2423</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47925</th>\n",
       "      <td>3898</td>\n",
       "      <td>2437</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47926</th>\n",
       "      <td>3898</td>\n",
       "      <td>3482</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47927</th>\n",
       "      <td>3919</td>\n",
       "      <td>2613</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47928</th>\n",
       "      <td>4039</td>\n",
       "      <td>2383</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>47929 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Start_grid  Stop_grid  Order_Cnt  Order_Sum  Prob\n",
       "0               0       2111          1         27  0.04\n",
       "1               0       2138          1         27  0.04\n",
       "2               0       2224          1         27  0.04\n",
       "3               0       2234          1         27  0.04\n",
       "4               0       2275          1         27  0.04\n",
       "5               0       2288          1         27  0.04\n",
       "6               0       2315          1         27  0.04\n",
       "7               0       2383          2         27  0.07\n",
       "8               0       2423          1         27  0.04\n",
       "9               0       2437          1         27  0.04\n",
       "10              0       2451          2         27  0.07\n",
       "11              0       2464          1         27  0.04\n",
       "12              0       2478          3         27  0.11\n",
       "13              0       2491          2         27  0.07\n",
       "14              0       2505          1         27  0.04\n",
       "15              0       2519          1         27  0.04\n",
       "16              0       2545          4         27  0.15\n",
       "17              0       2559          1         27  0.04\n",
       "18              0       2598          1         27  0.04\n",
       "19            264       2709          1          1  1.00\n",
       "20            328       2722          1          1  1.00\n",
       "21            437       2559          1          1  1.00\n",
       "22            439       2275          1          1  1.00\n",
       "23            504       2491          1          1  1.00\n",
       "24            564       2491          1          1  1.00\n",
       "25            584       2531          1          2  0.50\n",
       "26            584       2559          1          2  0.50\n",
       "27            587       2667          1          1  1.00\n",
       "28            591       2424          1          1  1.00\n",
       "29            610       1797          1          2  0.50\n",
       "...           ...        ...        ...        ...   ...\n",
       "47899        3784       2383          1          1  1.00\n",
       "47900        3789       2560          1          1  1.00\n",
       "47901        3803       2694          1          1  1.00\n",
       "47902        3806       2613          1          1  1.00\n",
       "47903        3810       2369          1          2  0.50\n",
       "47904        3810       2641          1          2  0.50\n",
       "47905        3819       2136          1          8  0.12\n",
       "47906        3819       2315          1          8  0.12\n",
       "47907        3819       2478          1          8  0.12\n",
       "47908        3819       2559          1          8  0.12\n",
       "47909        3819       2626          1          8  0.12\n",
       "47910        3819       2681          1          8  0.12\n",
       "47911        3819       2748          1          8  0.12\n",
       "47912        3819       2829          1          8  0.12\n",
       "47913        3830       2383          1          1  1.00\n",
       "47914        3845       2734          1          1  1.00\n",
       "47915        3849       2640          1          1  1.00\n",
       "47916        3857       2545          1          1  1.00\n",
       "47917        3867       2410          1          2  0.50\n",
       "47918        3867       2680          1          2  0.50\n",
       "47919        3893       2193          1          1  1.00\n",
       "47920        3898       1730          1          7  0.14\n",
       "47921        3898       2043          1          7  0.14\n",
       "47922        3898       2316          1          7  0.14\n",
       "47923        3898       2383          1          7  0.14\n",
       "47924        3898       2423          1          7  0.14\n",
       "47925        3898       2437          1          7  0.14\n",
       "47926        3898       3482          1          7  0.14\n",
       "47927        3919       2613          1          1  1.00\n",
       "47928        4039       2383          1          1  1.00\n",
       "\n",
       "[47929 rows x 5 columns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TRAN_PROB=OrderTran.groupby(['Start_grid','Stop_grid']).count()[['Order_id']]\n",
    "\n",
    "TRAN_PROB['Transition']=TRAN_PROB.index\n",
    "\n",
    "TRAN_PROB['Start_grid']=TRAN_PROB.apply(lambda x:x['Transition'][0],axis=1)\n",
    "\n",
    "TRAN_PROB['Stop_grid']=TRAN_PROB.apply(lambda x:x['Transition'][1],axis=1)\n",
    "\n",
    "TRAN_PROB=TRAN_PROB.reset_index(drop=True)\n",
    "\n",
    "TRAN_PROB=TRAN_PROB.rename(index=str, columns={\"Order_id\": \"Order_Cnt\"})\n",
    "\n",
    "TRAN_PROB=TRAN_PROB[['Start_grid','Stop_grid','Order_Cnt']]\n",
    "\n",
    "TEMP=OrderTran.groupby(['Start_grid']).count()[['Order_id']]\n",
    "\n",
    "TEMP['Start_grid']=TEMP.index\n",
    "\n",
    "TEMP=TEMP.rename(index=str, columns={\"Order_id\": \"Order_Sum\"})\n",
    "\n",
    "TEMP=TEMP.reset_index(drop=True)\n",
    "\n",
    "TEMP=TEMP[['Start_grid','Order_Sum']]\n",
    "\n",
    "TRAN_PROB=TRAN_PROB.merge(TEMP,on='Start_grid')\n",
    "\n",
    "TRAN_PROB['Prob']=TRAN_PROB.apply(lambda x:round(float(x['Order_Cnt']/x['Order_Sum']),2),axis=1)\n",
    "\n",
    "TRAN_PROB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2</th>\n",
       "      <td>19</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>8</td>\n",
       "      <td>02d3ca798e694d03</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.035714</td>\n",
       "      <td>1360</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.025000</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>16</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.352941</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.018868</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>11</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.025641</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>13</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.027027</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>14</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.024390</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>15</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.030303</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>17</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.178571</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>16</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>21</td>\n",
       "      <td>0436ee97262f993d</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.017241</td>\n",
       "      <td>0</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>21</td>\n",
       "      <td>02f776cf8965f27c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.020408</td>\n",
       "      <td>1128</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>22</td>\n",
       "      <td>0436ee97262f993d</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.125000</td>\n",
       "      <td>0</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>20</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.173913</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>8</td>\n",
       "      <td>8c80dbb01824b78f</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.023810</td>\n",
       "      <td>1373</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>21</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.074074</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>23</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>1428</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>6</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.014706</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>7</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.010309</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>8</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.015038</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>10</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.007692</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>11</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.012821</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>13</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.006849</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>17</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.020833</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>23</td>\n",
       "      <td>0436ee97262f993d</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.034483</td>\n",
       "      <td>0</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>18</td>\n",
       "      <td>2fdce81c8ce48731</td>\n",
       "      <td>00062a2f9c038b7c</td>\n",
       "      <td>0.008696</td>\n",
       "      <td>1251</td>\n",
       "      <td>1428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048545</th>\n",
       "      <td>3</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.916667</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048546</th>\n",
       "      <td>2</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048547</th>\n",
       "      <td>1</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.675676</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048548</th>\n",
       "      <td>0</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.476190</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048549</th>\n",
       "      <td>9</td>\n",
       "      <td>310fbbe806a00927</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.037736</td>\n",
       "      <td>3821</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048550</th>\n",
       "      <td>8</td>\n",
       "      <td>310fbbe806a00927</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.014925</td>\n",
       "      <td>3821</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048551</th>\n",
       "      <td>21</td>\n",
       "      <td>41db692ca1626039</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.027778</td>\n",
       "      <td>3688</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048552</th>\n",
       "      <td>7</td>\n",
       "      <td>310fbbe806a00927</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>3821</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048553</th>\n",
       "      <td>5</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.580645</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048554</th>\n",
       "      <td>6</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.041667</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048555</th>\n",
       "      <td>18</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.016051</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048556</th>\n",
       "      <td>17</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.003690</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048557</th>\n",
       "      <td>16</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.007407</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048558</th>\n",
       "      <td>15</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.003444</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048559</th>\n",
       "      <td>8</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.031496</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048560</th>\n",
       "      <td>9</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.042017</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048561</th>\n",
       "      <td>10</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.019231</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048562</th>\n",
       "      <td>11</td>\n",
       "      <td>7c29d6bc467bb809</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.076923</td>\n",
       "      <td>3803</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048563</th>\n",
       "      <td>18</td>\n",
       "      <td>45f06750e0bbff50</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.015152</td>\n",
       "      <td>3727</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048564</th>\n",
       "      <td>19</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.005747</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048565</th>\n",
       "      <td>13</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.009792</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048566</th>\n",
       "      <td>6</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.735484</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048567</th>\n",
       "      <td>7</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.475884</td>\n",
       "      <td>3757</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048568</th>\n",
       "      <td>11</td>\n",
       "      <td>3a448ce60f485541</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.006182</td>\n",
       "      <td>3677</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048569</th>\n",
       "      <td>16</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.022727</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048570</th>\n",
       "      <td>17</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.019231</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048571</th>\n",
       "      <td>18</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.075472</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048572</th>\n",
       "      <td>19</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.055556</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048573</th>\n",
       "      <td>11</td>\n",
       "      <td>310fbbe806a00927</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>3821</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048574</th>\n",
       "      <td>21</td>\n",
       "      <td>7270b0c919adb982</td>\n",
       "      <td>cbc2cb97f1de078d</td>\n",
       "      <td>0.037037</td>\n",
       "      <td>3746</td>\n",
       "      <td>3757</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1048575 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          0                 1                 2         3  OgnLoc  DstLoc\n",
       "0         9  000339fa73a27a67  000339fa73a27a67  1.000000       0       0\n",
       "1        14  170f1114ea9e3448  000339fa73a27a67  0.052632       0       0\n",
       "2        19  00062a2f9c038b7c  00062a2f9c038b7c  0.107143    1428    1428\n",
       "3        18  00062a2f9c038b7c  00062a2f9c038b7c  0.125000    1428    1428\n",
       "4         8  02d3ca798e694d03  00062a2f9c038b7c  0.035714    1360    1428\n",
       "5         9  8c80dbb01824b78f  00062a2f9c038b7c  0.025000    1373    1428\n",
       "6        16  00062a2f9c038b7c  00062a2f9c038b7c  0.352941    1428    1428\n",
       "7        10  8c80dbb01824b78f  00062a2f9c038b7c  0.018868    1373    1428\n",
       "8        11  8c80dbb01824b78f  00062a2f9c038b7c  0.025641    1373    1428\n",
       "9        13  8c80dbb01824b78f  00062a2f9c038b7c  0.027027    1373    1428\n",
       "10       14  8c80dbb01824b78f  00062a2f9c038b7c  0.024390    1373    1428\n",
       "11       15  8c80dbb01824b78f  00062a2f9c038b7c  0.030303    1373    1428\n",
       "12       17  00062a2f9c038b7c  00062a2f9c038b7c  0.178571    1428    1428\n",
       "13       16  8c80dbb01824b78f  00062a2f9c038b7c  0.033333    1373    1428\n",
       "14       21  0436ee97262f993d  00062a2f9c038b7c  0.017241       0    1428\n",
       "15       21  02f776cf8965f27c  00062a2f9c038b7c  0.020408    1128    1428\n",
       "16       22  0436ee97262f993d  00062a2f9c038b7c  0.125000       0    1428\n",
       "17       20  00062a2f9c038b7c  00062a2f9c038b7c  0.173913    1428    1428\n",
       "18        8  8c80dbb01824b78f  00062a2f9c038b7c  0.023810    1373    1428\n",
       "19       21  00062a2f9c038b7c  00062a2f9c038b7c  0.074074    1428    1428\n",
       "20       23  00062a2f9c038b7c  00062a2f9c038b7c  0.166667    1428    1428\n",
       "21        6  2fdce81c8ce48731  00062a2f9c038b7c  0.014706    1251    1428\n",
       "22        7  2fdce81c8ce48731  00062a2f9c038b7c  0.010309    1251    1428\n",
       "23        8  2fdce81c8ce48731  00062a2f9c038b7c  0.015038    1251    1428\n",
       "24       10  2fdce81c8ce48731  00062a2f9c038b7c  0.007692    1251    1428\n",
       "25       11  2fdce81c8ce48731  00062a2f9c038b7c  0.012821    1251    1428\n",
       "26       13  2fdce81c8ce48731  00062a2f9c038b7c  0.006849    1251    1428\n",
       "27       17  2fdce81c8ce48731  00062a2f9c038b7c  0.020833    1251    1428\n",
       "28       23  0436ee97262f993d  00062a2f9c038b7c  0.034483       0    1428\n",
       "29       18  2fdce81c8ce48731  00062a2f9c038b7c  0.008696    1251    1428\n",
       "...      ..               ...               ...       ...     ...     ...\n",
       "1048545   3  cbc2cb97f1de078d  cbc2cb97f1de078d  0.916667    3757    3757\n",
       "1048546   2  cbc2cb97f1de078d  cbc2cb97f1de078d  0.800000    3757    3757\n",
       "1048547   1  cbc2cb97f1de078d  cbc2cb97f1de078d  0.675676    3757    3757\n",
       "1048548   0  cbc2cb97f1de078d  cbc2cb97f1de078d  0.476190    3757    3757\n",
       "1048549   9  310fbbe806a00927  cbc2cb97f1de078d  0.037736    3821    3757\n",
       "1048550   8  310fbbe806a00927  cbc2cb97f1de078d  0.014925    3821    3757\n",
       "1048551  21  41db692ca1626039  cbc2cb97f1de078d  0.027778    3688    3757\n",
       "1048552   7  310fbbe806a00927  cbc2cb97f1de078d  0.020000    3821    3757\n",
       "1048553   5  cbc2cb97f1de078d  cbc2cb97f1de078d  0.580645    3757    3757\n",
       "1048554   6  7270b0c919adb982  cbc2cb97f1de078d  0.041667    3746    3757\n",
       "1048555  18  3a448ce60f485541  cbc2cb97f1de078d  0.016051    3677    3757\n",
       "1048556  17  3a448ce60f485541  cbc2cb97f1de078d  0.003690    3677    3757\n",
       "1048557  16  3a448ce60f485541  cbc2cb97f1de078d  0.007407    3677    3757\n",
       "1048558  15  3a448ce60f485541  cbc2cb97f1de078d  0.003444    3677    3757\n",
       "1048559   8  7270b0c919adb982  cbc2cb97f1de078d  0.031496    3746    3757\n",
       "1048560   9  7270b0c919adb982  cbc2cb97f1de078d  0.042017    3746    3757\n",
       "1048561  10  7270b0c919adb982  cbc2cb97f1de078d  0.019231    3746    3757\n",
       "1048562  11  7c29d6bc467bb809  cbc2cb97f1de078d  0.076923    3803    3757\n",
       "1048563  18  45f06750e0bbff50  cbc2cb97f1de078d  0.015152    3727    3757\n",
       "1048564  19  3a448ce60f485541  cbc2cb97f1de078d  0.005747    3677    3757\n",
       "1048565  13  3a448ce60f485541  cbc2cb97f1de078d  0.009792    3677    3757\n",
       "1048566   6  cbc2cb97f1de078d  cbc2cb97f1de078d  0.735484    3757    3757\n",
       "1048567   7  cbc2cb97f1de078d  cbc2cb97f1de078d  0.475884    3757    3757\n",
       "1048568  11  3a448ce60f485541  cbc2cb97f1de078d  0.006182    3677    3757\n",
       "1048569  16  7270b0c919adb982  cbc2cb97f1de078d  0.022727    3746    3757\n",
       "1048570  17  7270b0c919adb982  cbc2cb97f1de078d  0.019231    3746    3757\n",
       "1048571  18  7270b0c919adb982  cbc2cb97f1de078d  0.075472    3746    3757\n",
       "1048572  19  7270b0c919adb982  cbc2cb97f1de078d  0.055556    3746    3757\n",
       "1048573  11  310fbbe806a00927  cbc2cb97f1de078d  0.037037    3821    3757\n",
       "1048574  21  7270b0c919adb982  cbc2cb97f1de078d  0.037037    3746    3757\n",
       "\n",
       "[1048575 rows x 6 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''Grid Range'''\n",
    "\n",
    "IdleT=pd.read_csv('./Experiments/Demo/IdleT.csv')\n",
    "\n",
    "IdleT=IdleT.drop(columns=['Unnamed: 0'])\n",
    "\n",
    "IdleT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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